TR-2014-10
Racing and Pacing to Idle: Minimizing Energy Under Performance Constraints
David H. K. Kim; Henry Hoffmann. 21 May, 2014.
Communicated by Henry Hoffmann.
Abstract
The problem of minimizing energy for a real-time
performance constraint has been widely studied, both in
theory and in practice. Theoretical models have indicated large
potential energy savings, but practical concerns have made these
savings hard to realize. Instead, practitioners often rely on
the race-to-idle heuristic, which makes all resources available
to a task and then idles the system until the next task is
released. While this heuristic has proven effective, recent results
indicate that more sophisticated resource allocation schemes may
now provide greater energy savings. This paper investigates
resource allocation heuristics for real-time constraints using both
analytical and empirical techniques. We formalize the problem as
a linear program and develop a geometric interpretation, allowing
derivation of the optimality conditions for various heuristics. We
then demonstrate that the pace-to-idle heuristic is often better
and never worse than race-to-idle. We confirm these analytical
results by implementing a resource allocator based on the studied
heuristics and measuring energy consumption for eight different
applications on four different systems. The results confirm that
pace-to-idle produces better energy savings than race-to-idle, by
up to 20% on the newest platform in our study.
Original Document
The original document is available in PDF (uploaded 21 May, 2014 by
Henry Hoffmann).
